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ingestr

ingestr is a command-line application that ingests data from various sources and stores them in any database.

Worth itPyPI DatabaseReleased Aug 2026122.7K downloads / mopermissive licensePure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — ingestr-1.1.31-py3-none-any.whl
v1.1.31 · released 2026-08-14 · Python >=3.10

Yes. ingestr is worth installing if you need to move data between systems without writing custom code. It has low install friction, no runtime dependencies, active maintenance, a permissive license, and supports a broad ecosystem of sources and destinations. The CLI is straightforward, and the Python SDK is flexible enough for programmatic use. No known security vulnerabilities. The main gotcha is the Python 3.10+ requirement and the binary download on first SDK use.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires Python 3.10 or later.
  • The CLI binary is downloaded and cached on first Python SDK use.
  • Low install friction; pure Python wheel with no runtime dependencies.

License · maintenance · safety

permissive license (permissive) — MIT license (permissive) means you can use, modify, and distribute ingestr freely in commercial and private projects with minimal restrictions.

last release 2026-08-14 (0 days) · last repo commit 2026-08-14 · 3,839 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 122,724 downloads/mo, #11,938 on PyPI

Verify before relying

pip install ingestr

ingestr ingest \
  --source-uri 'postgresql://user:pass@host/db' \
  --source-table 'public.table' \
  --dest-uri 'duckdb:///warehouse.duckdb' \
  --dest-table 'main.table'
  • Whether the cached binary download works reliably behind corporate proxies or with network restrictions
  • Performance characteristics when moving very large datasets across different database types
  • Exact CDC (Change Data Capture) support scope beyond the three databases marked in the documentation
Same gist for agents: .md · .json

What it is and what it does

ingestr is a command-line data ingestion tool that eliminates the need to write custom code for moving data between systems. It handles the complexity of connecting to sources (databases, APIs, cloud platforms, files) and writing to destinations, accepting simple URI-based connection strings and table names. The tool supports incremental loading strategies—append, merge, or delete+insert—to handle common ETL patterns.

You can use it as a standalone CLI command or import it as a Python SDK. The Python SDK accepts lists of dictionaries, DataFrames, or generator functions as data sources, transporting them to destinations via Arrow IPC streams. It supports a wide range of sources (Postgres, MySQL, MongoDB, BigQuery, Snowflake, Kafka, CSV files, and many SaaS APIs) and destinations (most major databases and cloud storage systems), making it useful for ad-hoc migrations, regular syncs, and data warehouse loading.

Use it for

  • Migrate a PostgreSQL table to BigQuery without writing ETL code—just specify source and destination URIs.
  • Load data from a CSV file into DuckDB or Snowflake on a schedule using the CLI.
  • Sync MongoDB collections to a data warehouse with incremental merge logic to handle updates.
  • Ingest API data (e.g., from HubSpot, Stripe, or GitHub) into your analytics database in a single command.
  • Use the Python SDK to stream generator output (e.g., paginated API responses) directly to a database.
  • Set up CDC-based replication from MySQL or Postgres to keep a destination table in sync.

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

Worth it

Yes.

ingestr is worth installing if you need to move data between systems without writing custom code. It has low install friction, no runtime dependencies, active maintenance, a permissive license, and supports a broad ecosystem of sources and destinations. The CLI is straightforward, and the Python SDK is flexible enough for programmatic use. No known security vulnerabilities. The main gotcha is the Python 3.10+ requirement and the binary download on first SDK use.

Install

ingestr on PyPI

Before you install

Low install friction; pure Python wheel with no runtime dependencies. Active maintenance with recent releases and strong community engagement (3839 GitHub stars). Requires Python 3.10 or later.

Requires Python 3.10 or later. The CLI binary is downloaded and cached on first Python SDK use.

License in practice

MIT license (permissive) means you can use, modify, and distribute ingestr freely in commercial and private projects with minimal restrictions.

Quickstart

pip install ingestr

ingestr ingest \
  --source-uri 'postgresql://user:pass@host/db' \
  --source-table 'public.table' \
  --dest-uri 'duckdb:///warehouse.duckdb' \
  --dest-table 'main.table'

Verify before relying

  • Whether the cached binary download works reliably behind corporate proxies or with network restrictions
  • Performance characteristics when moving very large datasets across different database types
  • Exact CDC (Change Data Capture) support scope beyond the three databases marked in the documentation

Package facts

Licensepermissive license permissive
Python supportSupports the current Python release >=3.10
Install frictionLow. Pure-Python wheel
Runtime dependenciesNone
MaintenanceActively maintained 0 days since the last release
Last repo commit
First released
Downloads122,724 / month, #11,938 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Development Status :: 4 - BetaEnvironment :: ConsoleIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3Topic :: Database

Evidence: ingestr-1.1.31-py3-none-any.whl

Tags

Capabilities
data pipeline cli no codecopy database to databaseetl command line toolincremental data loadingdata ingestion without codemulti-source data syncdatabase migration tool
Topics
etl-clidata-migrationno-code

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See also unstructured-ingest · acryl-datahub · sonic-client · openmetadata-ingestion · azure-kusto-ingest · sling · gitingest · dlt · databricks-zerobus-ingest-sdk · django-postgres-copy